Unique features found on living-beings have been used for many years to characterize living-beings for identification. For example, fingerprints have long been used as a unique characteristic of each person for identification purposes. Other known methods of characterizing persons based on the same general principle involve voice pattern recognition, DNA testing and various other unique physical characteristics of human beings.
For physical items, unique features can be used to identify or characterize the physical item. Any manufacturing process for any physical item typically involves a sequence of process steps, such as chemical, mechanical, electrical or thermal. During the manufacturing process, these steps, based on the machinery and operating parameters, can create unique random minute surface features for each manufactured physical item. Such surface features cannot be replicated, controlled or eliminated under manufacturing conditions that may not use the exact same equipment or the exact same process steps and its defined parameters. Small variations can create different minute surface features that are unique from physical item to physical item.
Because random surface features, such as abrasion location, a particular surface roughness and the like, of a given material are unique, attempts have been made to capture various features as an intrinsic fingerprint to uniquely identify a particular object. Under this approach, a number of different systems and methods were attempted to detect unique intrinsic features of objects for determination of their authenticity. However, those systems have been unreliable, and unsuccessful. These methods have significant limitations, are difficult to implement and prone to false detections.
Pattern recognition of unique intrinsic features has been used in the past as an approach to identify objects. Under this approach, a number of different systems and methods were attempted to detect unique intrinsic features of objects for determination of their authenticity. In U.S. Patent Application US2010/0158377 (“377 disclosure”), characterization of materials like paper and plastics by generating signatures based on natural structured texture of the materials' surfaces is discussed.
The '377 disclosure discloses the use of laser light focused on an object's surface, the laser light reflected and collected to obtain information about the object's surface roughness. Although the information collected can then be processed to generate a unique identifying signature for the material, this process is significantly limiting and constrained because it requires not only the use of laser light, but also imaging of the same region of interest on each object, i.e. the imaging area has to be pre-selected for later comparison. It is necessary to use the same region of interest because different regions of interest on the given material's surface have different random patterns of microstructure encoded by detected speckle patterns, so the same region of interest must be compared for identification purpose. As well, the wavelength of the light used must be adjusted to match the expected feature size on the object. As a result multiple wavelengths of the light are required to work on different types of objects. These constraints mandate specialized efforts in orienting a pre-selected region of interest of an object and in adjusting illumination configurations and wavelength for different types of objects.
In U.S. Pat. No. 7,853,792 (“'792 patent”), a speckle pattern detection method is disclosed. The '792 patent describes that the micro topology of carton and paper using a coherent light source such as a laser beam is used for object authentication. However, the '792 patent is limited to speckle pattern detections of materials made of paper or cardboard. In addition, the use of a laser requires special equipment and efforts that are costly.
In U.S. Patent Application US 2008/0219503 (“503 disclosure”), a fingerprint for a given material can be generated by reading the random pattern of microstructure of the material on a defined region of interest. The '503 disclosure characterizes the material by acquiring an image of the material containing noise characteristics through illuminating the region of interest with diffused or specular light. The '503 disclosure requires special tailoring, i.e. varying resolutions of imaging for different classes of materials with different microstructure feature sizes, and special effort in orienting the region of interest. Moreover, the '503 disclosure also requires the region of interest to match some specific mathematical requirements to minimize false detections.
U.S. Patent Application US2011/0096955 attempts to resolve the issue of resolution, when using imaging devices with low resolution capacity for detecting counterfeits, by attaching macrolenses to a material's surface to enhance the resolution of microstructure of the surface. However, macrolenses for this purpose require additional components that increase the costs.
Diffuse lighting is common illumination approach, in which the light comes from many angles. Portraiture, macrophotography and outdoor scenes usually look best with diffuse lighting. However, for the purpose of characterizing objects via surface features, diffuse lighting produces a more uniform and smaller range of data values with reduced contrast that smooth out spatial structure. The prior art characterization devices and methods that use diffuse lighting do so because it tends to have a more uniform illumination, but such use suffers from the lack of data values with reduced contrast and is therefore unreliable.
Prior methods and devices for characterization of a given object employ extracting and evaluating natural randomness of the microstructure of an object's surface. To increase reliability special types of illumination are required. Certain defined regions of interest to be imaged and compared must be identified and pre-defined. Because of the varying microstructure feature size of the surface of different objects, special efforts in tailoring imagining configurations, such as wavelength of the light, resolution of imaging device or macrolenses, are required. Precise orientation of the region of interest is also required for comparison. Given these constraints, the prior art devices and methods are difficult to calibrate, difficult to implement and prone to false detections.